Instructions to use abhilash13/sql_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abhilash13/sql_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-7b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "abhilash13/sql_model") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from abhilash13/sql_model: direct link, hf CLI and curl.
- Browser
- Download file 167 Bytes
-
https://huggingface.co/abhilash13/sql_model/resolve/main/generation_config.json
- Command line
-
hf download hf://abhilash13/sql_model/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/abhilash13/sql_model/resolve/main/generation_config.json
167 Bytes
| { | |
| "bos_token_id": 151643, | |
| "eos_token_id": 151643, | |
| "max_length": 131072, | |
| "max_new_tokens": 2048, | |
| "pad_token_id": 151654, | |
| "transformers_version": "4.48.2" | |
| } | |